An Analysis of Optimal Training for Correlated Fading Channels Using Cutoff Rate

Report No. ARL-TR-3193
Authors: Saswat Misra, Ananthram Swami, and Lang Tong
Date/Pages: April 2004; 88 pages
Abstract: We consider the problem of optimal allocation of resources (power and bandwidth) between training and data for transmission over a Gauss- Markov fading channel. Inaccurate channel state information (CSI) is available at the receiver through periodic training. The transmitter is assumed to have knowledge of the channel Doppler spread. We compute the ergodic cutoff rate Ro for the temporally-correlated Rayleigh flatfading channels with imperfect channel state information (CSI) available at the receiver. We study MMSE estimators that predict the current channel state based on: all past pilot observations, only the most recent pilot observation, and the most recent and next in the future pilot observations. We analyze the optimal training energy and periodicity for each of these estimators. We show that optimizing the energy and periodicity of training results in significant energy savings over a sensible, but unoptimized, approach. The robustness of our analysis is tested for the case where the Doppler spread is known imperfectly at the transmitter. Additionally, we consider performance under the Jakes model.
Distribution: Approved for public release
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Last Update / Reviewed: April 1, 2004